如何在matplotlib中更改某些x轴刻度标签在底部x轴顶部的位置？

Question

这是我当前的脚本：

#!/usr/bin/env python3

import math
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

"""
Setup for a typical explanatory-style illustration style graph.
"""

h = 2
x = np.linspace(-np.pi, np.pi, 100)
y = 2 * np.sin(x)
rc = {
    # Tick in the middle of the axis line.
    'xtick.direction' : 'inout',
    'ytick.direction' : 'inout',

    # Bold is easier to read when we have few ticks.
    'font.weight': 'bold',
    'xtick.labelbottom': False,
    'xtick.labeltop': True,
}
with plt.rc_context(rc):
    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title(
        '2 sin(x), not $\\sqrt{2\\pi}$',
        # TODO make LaTeX part bold?
        # https://stackoverflow.com/questions/14324477/bold-font-weight-for-latex-axes-label-in-matplotlib
        fontweight='bold',
        # Too close otherwise.
        # https://stackoverflow.com/questions/16419670/increase-distance-between-title-and-plot-in-matplolib/56738085
        pad=20
    )

    # Custom visible plot area.
    # ax.set_xlim(-3, 3)
    ax.set_ylim(-2.5, 2.5)

    # Axes
    # Axes on center:
    # https://stackoverflow.com/questions/31556446/how-to-draw-axis-in-the-middle-of-the-figure
    ax.spines['left'].set_position('zero')
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_position('zero')
    ax.spines['top'].set_visible(False)
    # Axes with arrow:
    # https://stackoverflow.com/questions/33737736/matplotlib-axis-arrow-tip
    ax.plot(1, 0, ls="", marker=">", ms=10, color="k",
            transform=ax.get_yaxis_transform(), clip_on=False)
    ax.plot(0, 1, ls="", marker="^", ms=10, color="k",
            transform=ax.get_xaxis_transform(), clip_on=False)

    # Ticks
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('left')
    # Make ticks a bit longer.
    ax.tick_params(width=1, length=10)
    # Select tick positions
    # https://stackoverflow.com/questions/12608788/changing-the-tick-frequency-on-x-or-y-axis-in-matplotlib
    xticks = np.arange(math.ceil(min(x)),     math.floor(max(x)) + 1, 1)
    yticks = np.arange(math.ceil(min(y)) - 1, math.floor(max(y)) + 2, 1)
    # Remove 0.
    xticks = np.setdiff1d(xticks, [0])
    yticks = np.setdiff1d(yticks, [0])
    ax.xaxis.set_ticks(xticks)
    ax.yaxis.set_ticks(yticks)
    # Another approach. But because I want to be able to remove the 0,
    # anyways, I just explicitly give all ticks instead.
    # ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    # ax.yaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))

    # Annotations.
    ax.plot([0, np.pi/2], [h, h], '--r')
    ax.plot([np.pi/2, np.pi/2], [h, 0], '--r')
    ax.plot(np.pi/2, h, marker='o', linewidth=2, markersize=10,
        markerfacecolor='w', markeredgewidth=1.5, markeredgecolor='black')

plt.savefig(
    'main.png',
    format='png',
    bbox_inches='tight'
)
plt.clf()

这是输出：

这就是我想要的（使用GIMP破解），请注意负刻度标记现在在轴的另一侧了。

我尝试添加：

    for tick in ax.xaxis.get_majorticklabels():
        tick.set_verticalalignment("bottom")

如对How to move a tick's label in matplotlib?的回答所示，但这不能将刻度线标签向上移动得足够多，而是使标签显示在轴的顶部。

在matplotlib 3.2.2上测试。

Answer 1

以下代码将根据刻度线的垂直对齐方式来调整刻度线的垂直对齐方式。但是，这还不够，因为标签实际上锚定在刻度线的底部。因此，我需要稍微调整其y位置，但是您必须使用该值才能获得所需的输出

# adjust the xticks so that they are on top when x<0 and on the bottom when x≥0
ax.spines['top'].set_visible(True)
ax.spines['top'].set_position('zero')
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_position('zero')
ax.xaxis.set_tick_params(which='both', top=True, labeltop=True,
                             bottom=True, labelbottom=True)
fig.canvas.draw()
for tick in ax.xaxis.get_major_ticks():
    print(tick.get_loc())
    if tick.get_loc()<0:
        tick.tick1line.set_visible(False)
        tick.label1.set_visible(False)
    else:
        tick.tick2line.set_visible(False)
        tick.label2.set_visible(False)

完整代码：

import math
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

"""
Setup for a typical explanatory-style illustration style graph.
"""

h = 10
x = np.linspace(-np.pi, np.pi, 100)
y = h * np.sin(x)
rc = {
    # Tick in the middle of the axis line.
    'xtick.direction' : 'inout',
    'ytick.direction' : 'inout',

    # Bold is easier to read when we have few ticks.
    'font.weight': 'bold',
    'xtick.labelbottom': False,
    'xtick.labeltop': True,
}
with plt.rc_context(rc):
    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title(
        '2 sin(x), not $\\sqrt{2\\pi}$',
        # TODO make LaTeX part bold?
        # https://stackoverflow.com/questions/14324477/bold-font-weight-for-latex-axes-label-in-matplotlib
        fontweight='bold',
        # Too close otherwise.
        # https://stackoverflow.com/questions/16419670/increase-distance-between-title-and-plot-in-matplolib/56738085
        pad=20
    )

    # Custom visible plot area.
    # ax.set_xlim(-3, 3)
    ax.set_ylim(-2.5, 2.5)

    # Axes
    # Axes on center:
    # https://stackoverflow.com/questions/31556446/how-to-draw-axis-in-the-middle-of-the-figure
    ax.spines['left'].set_position('zero')
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_position('zero')
    ax.spines['top'].set_visible(False)
    # Axes with arrow:
    # https://stackoverflow.com/questions/33737736/matplotlib-axis-arrow-tip
    ax.plot(1, 0, ls="", marker=">", ms=10, color="k",
            transform=ax.get_yaxis_transform(), clip_on=False)
    ax.plot(0, 1, ls="", marker="^", ms=10, color="k",
            transform=ax.get_xaxis_transform(), clip_on=False)

    # Ticks
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('left')
    # Make ticks a bit longer.
    ax.tick_params(width=1, length=10)
    # Select tick positions
    # https://stackoverflow.com/questions/12608788/changing-the-tick-frequency-on-x-or-y-axis-in-matplotlib
    xticks = np.arange(math.ceil(min(x)),     math.floor(max(x)) + 1, 1)
    yticks = np.arange(math.ceil(min(y)) - 1, math.floor(max(y)) + 2, 1)
    # Remove 0.
    xticks = np.setdiff1d(xticks, [0])
    yticks = np.setdiff1d(yticks, [0])
    ax.xaxis.set_ticks(xticks)
    ax.yaxis.set_ticks(yticks)
    # Another approach. But because I want to be able to remove the 0,
    # anyways, I just explicitly give all ticks instead.
    # ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    # ax.yaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    
    for g,t in zip(ax.get_xticks(),ax.get_xticklabels()):
        if g<0:
            t.set_va('bottom')
        else:
            t.set_va('top')
        t.set_transform(ax.transData)
        t.set_position((g,0.15*-(g/abs(g))))

    # Annotations.
    ax.plot([0, np.pi/2], [h, h], '--r')
    ax.plot([np.pi/2, np.pi/2], [h, 0], '--r')
    ax.plot(np.pi/2, h, marker='o', linewidth=2, markersize=10,
        markerfacecolor='w', markeredgewidth=1.5, markeredgecolor='black')
    
    
    # adjust the xticks so that they are on top when x<0 and on the bottom when x≥0
    ax.spines['top'].set_visible(True)
    ax.spines['top'].set_position('zero')
    ax.spines['bottom'].set_visible(True)
    ax.spines['bottom'].set_position('zero')
    ax.xaxis.set_tick_params(which='both', top=True, labeltop=True,
                                 bottom=True, labelbottom=True)
    fig.canvas.draw()
    for tick in ax.xaxis.get_major_ticks():
        print(tick.get_loc())
        if tick.get_loc()<0:
            tick.tick1line.set_visible(False)
            tick.label1.set_visible(False)
        else:
            tick.tick2line.set_visible(False)
            tick.label2.set_visible(False)